Search results for "Probabilistic"

Strategies for Improving Optimal Positioning of Quality Sensors in Urban Drainage Systems for Non-Conservative Contaminants

2021

In the urban drainage sector, the problem of polluting discharges in sewers may act on the proper functioning of the sewer system, on the wastewater treatment plant reliability and on the receiving water body preservation. Therefore, the implementation of a chemical monitoring network is necessary to promptly detect and contain the event of contamination. Sensor location is usually an optimization exercise that is based on probabilistic or black-box methods and their efficiency is usually dependent on the initial assumption made on possible eligibility of nodes to become a monitoring point. It is a common practice to establish an initial non-informative assumption by considering all network…

ON-LINE CONSTRUCTION OF A SMALL AUTOMATON FOR A FINITE SET OF WORDS

2012

In this paper we describe a "light" algorithm for the on-line construction of a small automaton recognising a finite set of words. The algorithm runs in linear time. We carried out good experimental results on real dictionaries, on biological sequences and on the sets of suffixes (resp. factors) of a set of words that shows how our automaton is near to the minimal one. For the suffixes of a text, we propose a modified construction that leads to an even smaller automaton. We moreover construct linear algorithms for the insertion and deletion of a word in a finite set, directly from the constructed automaton.

The challenge of using the rheumatoid arthritis diagnostic criteria in clinical practice.

2015

The new 2010 ACR/EULAR (American College of Rheumatology/European League Against Rheumatism) criteria of Rheumatoid Arthritis recently published, have been released to classify and identify patients with early RA who could benefit from early therapy. They recommend anti-citrullinated protein antibody (ACPA) testing as an alternative criterion to Rheumatoid Factor (RF) and ACPA that were introduced together with the other classic criteria in a scoring system. We previously criticized these new criteria because of unavailable specificity and sensibility in the first paper, and the use of ACPA as dichotomous criterion (presence/absent) and alternatives to rheumatoid factor. Our previous work p…

A probabilistic long‐term framework for site‐specific erosion analysis of wind turbine blades: A case study of 31 Dutch sites

2021

Abstract Rain‐induced leading‐edge erosion (LEE) of wind turbine blades (WTBs) is associated with high repair and maintenance costs. The effects of LEE can be triggered in less than 1 to 2 years for some wind turbine sites, whereas it may take several years for others. In addition, the growth of erosion may also differ for different blades and turbines operating at the same site. Hence, LEE is a site‐ and turbine‐specific problem. In this paper, we propose a probabilistic long‐term framework for assessing site‐specific lifetime of a WTB coating system. Case studies are presented for 1.5 and 10 MW wind turbines, where geographic bubble charts for the leading‐edge lifetime and number of repai…

Comparison between unrestricted dynamic shakedown design and a new probabilistic approach for structures under seismic loadings

2014

The paper concerns a study related to the comparison between two different approaches utilized for the formulation of an optimal shakedown design problem for elastic plastic frame structures subjected to a combination of fixed and seismic loading. The first formulation utilizes the unrestricted dynamic shakedown theory, while the second one is based on a new probabilistic approach. The comparison is effected in terms of mathematical formulations, in terms of adopted loading models and in terms of numerical results. The performed applications are related to plane steel frames.

Image classification based on 2D feature motifs

2013

The classification of raw data often involves the problem of selecting the appropriate set of features to represent the input data. In general, various features can be extracted from the input dataset, but only some of them are actually relevant for the classification process. Since relevant features are often unknown in real-world problems, many candidate features are usually introduced. This degrades both the speed and the predictive accuracy of the classifier due to the presence of redundancy in the candidate feature set. In this paper, we study the capability of a special class of motifs previously introduced in the literature, i.e. 2D irredundant motifs, when they are exploited as feat…

Mappatura probabilistica della pericolosità idraulica: analisi dell’incertezza legata all’utilizzo di un approccio bivariato per l’analisi di frequen…

2014

Probabilistic Evaluation of the Adaptation Time for Structures under Seismic Loads

2016

Abstract In this paper, a probabilistic approach for the evaluation of the adaptation time for elastic perfectly plastic frames is proposed. The considered load history acting on the structure is defined as a suitable combination of quasi-statical loads and seismic actions. The proposed approach utilizes the Monte Carlo method in order to generate a suitable large number of seismic acceleration histories and for each one the related load combination is defined. Furthermore, for each load combination the related adaptation time is determined, if any, as the optimal one for which the structure is able to shakedown under the unamplified applied actions. A known generalized Ceradini's theorem i…

Algorithms for coherence checking and propagation of conditional probability bounds

2001

In this paper, we propose some algorithms for the checking of generalized coherence (g-coherence) and for the extension of imprecise conditional probability assessments. Our concept of g-coherence is a generalization of de Finetti’s coherence principle and is equivalent to the ”avoiding uniform loss” property for lower and upper probabilities (a la Walley). By our algorithms we can check the g-coherence of a given imprecise assessment and we can correct it in order to obtain the associated coherent assessment (in the sense of Walley and Williams). Exploiting some properties of the random gain we show how, in the linear systems involved in our algorithms, we can work with a reduced set of va…

GRANULAR-INFORMATION-BASED RISK ANALYSIS IN UNCERTAIN SITUATIONS

2006

In the real life almost all of the decisions that we have to make incorporate uncertainty about the future events. Assessment of the uncertainty and, thus, the risk that is inherent in these decisions models can be critical. It is even truer if we are talking about the possibility of negative impact on the environment. It is very important to assess all the environmental risks in a project if there is any hazard to the environment. In this paper the possibility of using granular information is considered. The main advantage of the granular information is that it can be used to assess risks in situations when information about future events is incomplete and imprecise. Moreover, we can use n…